Backend Engineer - Machine Learning Systems - Japan

Responsibilities

About Doubao (Seed)

Founded in 2023, the ByteDance Doubao (Seed) Team is dedicated to pioneering advanced AI foundation models. Our goal is to lead in cutting-edge research and drive technological and societal advancements.

With a strong commitment to AI, our research areas span deep learning, reinforcement learning, Language, Vision, Audio, AI Infra, and AI Safety. Our team has labs and research positions across China, Singapore, and the US.

Leveraging substantial data and computing resources, and through continued investment in these domains, we have developed a proprietary general-purpose model with multimodal capabilities. In the Chinese market, Doubao models power over 50 ByteDance apps and business lines, including Doubao, Coze, and Dreamina, and are available to external enterprise clients via Volcano Engine. Today, the Doubao app stands as the most widely used AIGC application in China.

Why Join Us

Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible.

Together, we inspire creativity and enrich life - a mission we aim towards achieving every day.

To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.

At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve.

Join us.

About the team

The ByteDance Large Model Team is committed to developing the most advanced AI large model technology in the industry, becoming a world-class research team, and contributing to technological and social development. The Large Model Team has a long-term vision and determination in the field of AI, with research directions covering NLP, CV, speech, and other areas. Relying on the abundant data and computing resources of the platform, the team has continued to invest in relevant fields and has launched its own general large model, providing multi-modal capabilities.

The Machine Learning (ML) System sub-team combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and inference system/services worldwide, providing high-performance, highly reliable, scalable systems for LLM/AIGC/AGI.

In our team, you'll have the opportunity to build the large-scale heterogeneous system integrating with GPU/NPU/RDMA/Storage and keep it running steadily and reliably, enrich your expertise in coding, performance analysis, and distributed system, and be involved in the decision-making process. You'll also be part of a global team with members from the United States, China, and Singapore working collaboratively towards a unified project direction.

• Responsible for the design and development of Machine Learning infrastructure and platform services for model development, training, and deployment;
• Build and deploy large-scale systems for machine learning integrating with GPUs, RDMA networking, and high-performance storage;
• Design and develop resource orchestration and workload scheduling in global data centers for online and offline scenarios;
• Manage a large number of GPU resources to ensure computing powers are efficiently allocated to different business lines;
• Be the expert in providing technical solutions and consultations to business users for issues such as high stability and availability of the system;
• Be the go-to expert to drive project deliverables for system and services construction with cross-functional teams such as the business team, data center team, network team, computing team, storage team;
• Research, design, and develop computer and network software or specialized utility programs;
• Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis;
• Update software, enhance existing software capabilities, and develop and direct software testing and validation procedures;
• Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements;

Qualifications

Minimum Qualifications:

• Bachelor's degree or above, major in Computer Science, computer engineering, or related;
• At least 3 years of working experience in at least one programming language such as C++/Go/Python/Shell in Linux environment;
• Proven experience in contributing to large-scale systems, multi-tenant systems including architecture, reliability, and scaling;
• Strong hands-on experience with Kubernetes architecture, and possess rich experience in system-level development and tuning;
• Excellent logical analysis ability, able to reasonably abstract and split business logic;
• Strong sense of responsibility, good learning ability, communication skills, and self-drive; good team spirit.

Preferred Qualifications:

• Familiar with the ML Infrastructure of Large Model training and inference;
• Familiar with front-end and back-end technologies, such as Django / Flask / NodeJS / React, etc.;
• Experience in one of the following fields: AI Infrastructure, HW/SW Co-Design, High Performance Computing, ML Hardware Architecture (GPU, Accelerators, Networking).

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